Kriging and masurement errors

István Fazekas; Alexander G. Kukush

Discussiones Mathematicae Probability and Statistics (2005)

  • Volume: 25, Issue: 2, page 139-159
  • ISSN: 1509-9423

Abstract

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A linear geostatistical model is considered. Properties of a universal kriging are studied when the locations of observations aremeasured with errors. Alternative prediction procedures are introduced and their least squares errors are analyzed.

How to cite

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István Fazekas, and Alexander G. Kukush. "Kriging and masurement errors." Discussiones Mathematicae Probability and Statistics 25.2 (2005): 139-159. <http://eudml.org/doc/287696>.

@article{IstvánFazekas2005,
abstract = {A linear geostatistical model is considered. Properties of a universal kriging are studied when the locations of observations aremeasured with errors. Alternative prediction procedures are introduced and their least squares errors are analyzed.},
author = {István Fazekas, Alexander G. Kukush},
journal = {Discussiones Mathematicae Probability and Statistics},
keywords = {universal kriging; least squares; errors-in-variables},
language = {eng},
number = {2},
pages = {139-159},
title = {Kriging and masurement errors},
url = {http://eudml.org/doc/287696},
volume = {25},
year = {2005},
}

TY - JOUR
AU - István Fazekas
AU - Alexander G. Kukush
TI - Kriging and masurement errors
JO - Discussiones Mathematicae Probability and Statistics
PY - 2005
VL - 25
IS - 2
SP - 139
EP - 159
AB - A linear geostatistical model is considered. Properties of a universal kriging are studied when the locations of observations aremeasured with errors. Alternative prediction procedures are introduced and their least squares errors are analyzed.
LA - eng
KW - universal kriging; least squares; errors-in-variables
UR - http://eudml.org/doc/287696
ER -

References

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  1. [1] O. Berke, On spatiotemporal prediction for on-line monitoring data, Comm. Statist. Theory Methods 27 (9) (1998), 2343-2369. Zbl0907.62099
  2. [2] N.A.C. Cressie, Statistics for Spatial Data, Wiley, New York 1991. Zbl0799.62002
  3. [3] I. Fazekas, S. Baran, A.G. Kukush, and J. Lauridsen, Asymptotic properties in space and time of an estimator in nonlinear functional errors-in-variables models, Random Oper. Stoch. Equ. 7 (4) (1999), 389-412. Zbl0953.62061
  4. [4] I. Fazekas and A.G. Kukush, Errors-in-variables and kriging, Proc. 4th International Conference on Applied Informatics, Eger 1999, 261-273. Zbl1003.62083
  5. [5] J. Gabrosek and N. Cressie, The effect on attribute prediction of locationuncertainity in spatial data, Geographical Analysis 34 (3) (2002), 261-285. 
  6. [6] D.G. Krige, A statistical approach to some basic mine valuations problems on the Witwatersrand, Journal of the Chemical, Metallurgical and Mining Society of South Africa 52 (1951), 119-139. 
  7. [7] S.J. Yakowitz and F. Szidarovszky, A comparison of kriging with nonparametric regression methods, J. Multivariate Anal. 16 (1985), 21-53. Zbl0591.62060

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